Machine Learning for Analysis of Microscopy Images: A Practical Guide

Vadim Zinchuk; Olga Grossenbacher‐Zinchuk

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Machine Learning for Analysis of Microscopy Images: A Practical Guide

机译：用于分析显微镜图像的机器学习图像：实用指南

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The explosive growth of machine learning has provided scientists with insights into data in ways unattainable using prior research techniques. It has allowed the detection of biological features that were previously unrecognized and overlooked. However, because machine‐learning methodology originates from informatics, many cell biology labs have experienced difficulties in implementing this approach. In this article, we target the rapidly expanding audience of cell and molecular biologists interested in exploiting machine learning for analysis of their research. We discuss the advantages of employing machine learning with microscopy approaches and describe the machine‐learning pipeline. We also give practical guidelines for building models of cell behavior using machine learning. We conclude with an overview of the tools required for model creation, and share advice on their use.

机译：机器学习的爆炸性增长为科学家提供了利用现有研究技术无法实现的数据洞察。它允许检测以前未被识别和忽视的生物学特征。然而，由于机器学习方法来自信息学，所以许多细胞生物学实验室在实施这种方法方面经历了困难。在本文中，我们针对迅速扩张的细胞和分子生物学家有兴趣利用机器学习以分析他们的研究。我们讨论了用显微镜接近使用机器学习的优点，并描述了机器学习管道。我们还提供了使用机器学习建立细胞行为模型的实用指南。我们结束了概述了模型创建所需的工具，并与他们的使用分享建议。

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《Current Protocols in Cell Biology》 |2020年第1期|共14页
作者
Vadim Zinchuk; Olga Grossenbacher‐Zinchuk;
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作者单位

Department of Neurobiology and Anatomy Kochi University Faculty of Medicine Kochi Japan;

Clinical &

Medical Affairs Ziemer Ophthalmic Systems AG Port Switzerland;

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正文语种 eng
中图分类细胞生物学;
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1. Machine Learning for Analysis of Microscopy Images: A Practical Guide [J] . Vadim Zinchuk, Olga Grossenbacher‐Zinchuk Current Protocols in Cell Biology . 2020,第1期

机译：用于分析显微镜图像的机器学习图像：实用指南
2. Machine learning for locating organic matter and pores in scanning electron microscopy images of organic-rich shales [J] . Wu Yaokun, Misra Siddharth, Sondergeld Carl, Fuel . 2019,第Octa1期

机译：机器学习用于在富含有机物的页岩的扫描电子显微镜图像中定位有机物和孔隙
3. Automated Neuron Detection in High-Content Fluorescence Microscopy Images Using Machine Learning [J] . Mata Gadea, Radojevic Miroslav, Fernandez-Lozano Carlos, Neuroinformatics . 2019,第2期

机译：使用机器学习的高含量荧光显微镜图像中自动神经元检测
4. Using Machine Learning for Automatic Estimation of M. Smegmatis Cell Count from Fluorescence Microscopy Images [C] . Daniel Vente, Ognjen Arandjelovic, Vincent O. Baron, Health intelligence and medicine . 2019

机译：使用机器学习从荧光显微镜图像自动估计耻垢分枝杆菌的细胞计数
5. Flow Imaging Microscopy and Machine Learning Methods and Applications for Particle Morphology Analysis [D] . Daniels, Austin Lewis. 2021

机译：流量成像显微镜和机器学习方法和应用粒子形态分析
6. Erratum to: ‘Aro: a machine learning approach to identifying single molecules and estimating classification error in fluorescence microscopy images’ [O] . Allison Chia-Yi Wu, Scott A. Rifkin 2016

机译：勘误至： Aro：一种用于识别荧光显微镜图像中单分子并估计分类错误的机器学习方法
7. The Bioinformatics Bookshelf: Teach Yourself Computational Biology? Bioinformatics: The Machine Learning Approach By Pierre Baldi and Soren Brunak Cambridge, MA: MIT Press (1998). 351 pp. $40.00; Bioinformatics: A Practical Guide to the Analysis of Genes and Proteins Edited by Andreas D. Baxevanis and B. F. Francis Ouellette New York: Wiley-lnterscience (1998). 370 pp. $59.95; Guide to Human Genome Computing, Second Edition Edited by Martin J. Bishop San Diego, CA: Academic Press (1998). 306 pp. $69.95; Biological Sequence Analysis: Probabilistic Models of Proteins and Nucleic Acids By Richard Durbin, Sean Eddy, Anders Krogh, and Graeme Mitchison Cambridge: Cambridge University Press (1998). 356 pp. $34.95; Algorithms on Strings, Trees, and Sequences: Computer Science and Computational Biology By Dan Gusfield Cambridge: Cambridge University Press (1997). 534 pp. $59.95; Introduction to Computational Molecular Biology By Joao Setubal and Joao Meidanis Boston: PWS Publishing (1997). 296 pp. $61.95 [O] . Pickeral Oxana K, Boguski Mark S 1999

机译：生物信息学书架：自学计算生物学吗？生物信息学：机器学习方法，作者：Pierre Baldi和Soren Brunak剑桥，麻省：麻省理工学院出版社（1998）。 351页，$ 40.00；生物信息学：由Andreas D. Baxevanis和B. F. Francis Ouellette编辑的基因和蛋白质分析实用指南纽约：Wiley-Interscience（1998）。 370页，$ 59.95；《人类基因组计算指南》，第二版，由马丁·J·毕晓普（Martin J. Bishop）编辑，加利福尼亚州圣地亚哥：学术出版社（1998）。 306页，$ 69.95；生物序列分析：蛋白质和核酸的概率模型Richard Durbin，Sean Eddy，Anders Krogh和Graeme Mitchison剑桥：剑桥大学出版社（1998年）。 356页，$ 34.95；字符串，树和序列上的算法：计算机科学和计算生物学Dan Danssfield剑桥：剑桥大学出版社（1997年）。 534页，$ 59.95； Joao Setubal和Joao Meidanis Boston撰写的《计算分子生物学概论》：PWS出版（1997）。 296羽61.95美元

Machine Learning for Analysis of Microscopy Images: A Practical Guide

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